EDITOR ’ S QUESTION
HOW SHOULD REGIONAL ENTERPRISES BEGIN THEIR ENTERPRISE-WIDE AI AND GENAI JOURNEY OF ADOPTION WITH A BUSINESS FOCUS AND WHAT ARE SOME OF THE BEST PRACTICES THAT CAN BE ADOPTED ?
We are now in a position to evaluate GenAI by looking at its various proven use cases . It is capable of idea generation , taking part in brainstorming just as humans can . It can rate , rank , and recommend , summarizing huge data sources into useful reports and journals and give advice backed by chains of logic , as human consultants can do . Executives from HPE , Netskope , Dataiku , Kissflow , ServiceNow , respond .
MOHAMMAD AL-JALLAD , CTO AND DIRECTOR , UK , IRELAND ,
MIDDLE EAST AND AFRICA , HPE
AI holds immense potential for enterprise transformation , but the complexities of fragmented AI technology contain too many risks and barriers that hamper large-scale enterprise adoption and can jeopardise a company ’ s most valuable asset , its proprietary data . To unleash the immense potential of AI and specifically generative AI , GenAI , organisations need to have the right infrastructure in place . Those who are only at the starting point of their AI journey should adopt simple , turnkey solutions which enable the organisation , regardless of size , to gain a fast and flexible path for sustainably developing and deploying energy-efficient AI applications . This , in turn , allows them to focus their resources on developing new AI use cases that can boost productivity and unlock new revenue streams .
A best practice when adopting GenAI is to consider simple infrastructure observability across your current IT estate . Enterprises need to be able to analyse large datasets for insights , but this can often hinder productivity and operations management . By using GenAI to analyse these datasets and answer questions with a conversational assistant , enterprises can focus on their adoption of AI .
It is also recommended for enterprises to tap into existing ecosystems that can help them in their GenAI adoption . It is important that they invest in their teams and channel partners . By training and accessing global networks of system integrators , enterprises across a variety of industries have support to run complex AI workloads . Choosing the right software can help access a ready to run set of curated AI and data foundation tools which can provide adaptable solutions , ongoing enterprise support , and trusted AI services . These include data and model compliance , and extensible features that ensure AI pipelines are compliant , explainable and reproducible throughout the AI lifecycle .
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